Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios

Renewable energy integration into existing or new energy hubs together with Green technologies such as Power to Gas and Green Hydrogen has become essential because of the aim of keeping the average global temperature rise within 2 ^°C with regard to the Paris Agreement. Hence, all energy markets are expected to face substantial transitions worldwide. On the other hand, investigation of renewable energy systems integrated with green chemical conversion, and in particular combination of green hydrogen and synthetic methanation, is still a scarce subject in the literature in terms of optimal and simultaneous design and operation for integrated energy grids under weather intermittency and demand uncertainty. In fact, the integration of such promising new technologies has been studied mainly in the operational phase, without considering design and management simultaneously. Thus, in this work, a multi-period mixed-integer linear programming (MILP) model is formulated to deal with the aforementioned challenges. Under current carbon dioxide limitations dictated by the Paris Agreement, this model computes the best configuration of the renewable and non-renewable-based generators, their optimal rated powers, capacities and scheduling sequences from a large candidate pool containing thirty-nine different equipment simultaneously. Moreover, the effect of the intermittent nature of renewable resources is analyzed comprehensively under three different scenarios for a specific location. Accordingly, a practical scenario generation method is proposed in this work. It is observed that photovoltaic, oil co-generator, reciprocating ICE, micro turbine, and bio-gasifier are the equipment that is commonly chosen under the three different scenarios. Results also show that concepts such as green hydrogen and power-to-gas are currently not preferable for the investigated location. On the other hand, analysis shows that if the emission limits are getting tightened, it is expected that constructing renewable resource-based grids will be economically more feasible.     

Modification of the wood-plastic composite for enhancement of formaldehyde clearance and the 3D printing application

As the formaldehyde is one of the main indoor pollutants, the purpose of this study is to effectively remove indoor formaldehyde pollution by using environmentally friendly 3D printing ornaments. The wood 3D printing filaments cellulose/polylactic acid composite (Cellu/P) was selected as the starting material, and 3-aminopropyltriethoxysilane (APTES) was used for chemical modification to obtain a series of cellulose composite materials with amino groups. The modified composite materials (APTES@Cellu/P) were characterized by Fourier transform infrared, X-ray diffraction, scanning electron microscope, energy dispersive spectroscopy, thermogravimetric analysis, and mechanical tests, and a formaldehyde removal experiment was performed. The feasibility of 3D printing was evaluated, and the process of 3D printing-functionalized customized ornaments was proposed, and then a school emblem was used for modeling, printing, and surface modification. Compared with the commercially traditional activated carbon, 3D printing-customized ornaments of APTES@Cellu/P material has a better formaldehyde removal effect, and can even avoid the secondary pollution that is common to the activated carbon.     

AAOA-MBR工艺在工程中的应用分析

通过对AAOA-MBR工艺在实际工程中的应用,分析该工艺处理城市污水的节能减排效能。实践表明AAOA-MBR工艺具有很强的抗冲击负荷能力,在进水质水量大幅度波动、且碳源匮乏的情况下,仍能取得良好的处理效果。实际工程运行四年来,厂区出水各项指标均稳定优于城镇污水处理厂污染物排放标准(GB 18918-2002)中的一级A标准,其中COD、BOD₅、SS、NH₃^-N去除率分别达到可分别达到90.14%、98.25%、95.58%和98.2%;通过对运行期间污水处理量与耗电量相关关系进行回归分析可知,当处理水量达到设计规模时,其吨水耗电量预测为0.31kWh/m³。同时,基于对污水处理系统的沿程水质检测,优化进水水量分配和内循环回流比并进行产水泵联动改造,可进一步提高系统节能减排效果。     

Bioinspired Triboelectric Soft Robot Driven by Mechanical Energy

A sustainable power source is a key technical challenge for practical applications of electrically responsive soft robots, especially the required voltage is over several thousand volts. Here, a practicable new technology, triboelectric soft robot (TESR) system with the primary characteristics of power source from mechanical energy, is developed. At its heart is TESR with bioinspired architectures made of soft-deformable body and two triboelectric adhesion feet, which is driven and accurately controlled through triboelectric effect, while reaching maximum crawling speeds of 14.9 mm s⁻¹ on the acrylic surface. The characteristics of the TESR, including displacement and force, are tested and simulated under the power of a rotary freestanding triboelectric nanogenerator (RF-TENG). Crawling of TESR is successfully realized on different materials surfaces and different angle slopes under the driven of RF-TENG. Furthermore, a real-time visual monitoring platform, in which TESR carries a micro camera to transmit images in a long narrow tunnel, is also achieved successfully, indicating that it can be used for fast diagnosis in an area inaccessible to human beings in the future. This study offers a new insight into the sustainable power source technologies suitable for electrically responsive soft robots and contributes to expanding the applicability of TENGs.     

Hydrogen production by hybrid system and its conversion by fuel cell in Algeria; Djanet

In this work we present a scenario of wind and solar energy production and seasonal energy storage producing Hydrogen in Djanet (East-South of Algeria). In addition we suppose assume the use of a set of fuel cells which are connected to the grid to provide a supply of energy when needed afterwards. The aim of this primary study is giving an alternative solution for the electric production in Djanet, which is mainly based on diesel generator. For that we made an investigation to highlight the potential of renewable energy production in this region. To ascertain feasibility of one hybrid system, we made energetic assessment considering the real climatic conditions of Djanet.     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.     

计及时间相关性的微能源网鲁棒规划方法

微能源网以能源的梯级利用为原则,可实现风、光等多种新能源的高比例消纳,满足区域内电、热、冷等多种能源需求。微能源网中存在新能源出力与冷、热、电负荷的多重不确定性。为增强系统规划结果的鲁棒性,常采用不确定集表述新能源出力与多种用能需求的不确定性,实现针对微能源网的鲁棒规划设计,往往使系统规划结果过于保守,降低系统经济性。为克服以上问题,规避实际运行中不可能发生的场景,降低系统规划结果的保守性,文章提出一种考虑时间相关性的微能源网鲁棒规划模型。该模型在计及多重源荷不确定性的基础上,进一步考虑新能源出力与冷、热、电负荷的时间相关性。通过算例对传统不确定集与所提出的改进不确定集进行对比分析,验证了所提模型及方法的优越性和有效性。     

A comprehensive review of renewable energy resources for electricity generation in Australia

Recently, renewable energy resources and their impacts have sparked a heated debate to resolve the Australian energy crisis. There are many projects launched throughout the country to improve network security and reliability. This paper aims to review the current status of different renewable energy resources along with their impacts on society and the environment. Besides, it provides for the first time the statistics of the documents published in the field of renewable energy in Australia. The statistics include information such as the rate of papers published, possible journals for finding relative paper, types of documents published, top authors, and the most prevalent keywords in the field of renewable energy in Australia. It will focus on solar, wind, biomass, geothermal and hydropower technologies and will investigate the social and environmental impacts of these technologies.     

Economic Evaluation of Power System Flexibility by Commercial Air Conditioner Control with Large Penetration of Photovoltaic Generation

High penetration of intermittent renewable energy such as photovoltaic (PV) and wind power could cause shortage of power system flexibility. Demand response is expected to help supply ancillary service instead of the conventional power plant. Commercial air conditioners are a promising responsive load for demand response because they account for a large proportion of power consumption in the power system. We calculate a system operation cost and hourly operation pattern of each power plant by using the optimal power generation model considering flexibility supply from controlling commercial air conditioner. We obtained the following results as an effect of commercial air conditioner control. (1) The power generation of oil fired power plants decreases at peak time and annual fuel cost of oil fired plant is reduced by approximately 30% at most in Kanto area. (2) The percentage of rated operation mode of LNG combined cycle plants increases. (3) Curtailed energy rate of PV decreases because a power storage amount by pumped hydropower generation increases. (4) Required battery capacity to reduce PV curtailed amount decreased by combining battery energy storage system in case of high penetration of PV.